Key Information
About the content
This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
Syllabus
- Part 1 – Designing studies
- Part 2 – Exploratory data analysis
- Part 3 – Introduction to inference via simulation
- Part 1 – Defining probability
- Part 2 – Conditional probability
- Part 3 – Normal distribution
- Part 4 – Binomial distribution
- Part 1 – Variability in estimates and the Central Limit Theorem
- Part 2 – Confidence intervals
- Part 3 – Hypothesis tests
- Part 4 – Inference for other estimators
- Part 5 - Decision errors, significance, and confidence
- Part 1 – t-inference
- Part 2 – Power
- Part 3 – Comparing three or more means (ANOVA)
- Part 4 – Simulation based inference for means
- Part 1 – Single proportion
- Part 2 – Comparing two proportions
- Part 3 – Inference for proportions via simulation
- Part 4 – Comparing three or more proportions (Chi-square)
- Part 1 – Relationship between two numerical variables
- Part 2 – Linear regression with a single predictor
- Part 3 – Outliers in linear regression
- Part 4 – Inference for linear regression
- Part 1 – Regression with multiple predictors
- Part 2 – Inference for multiple linear regression
- Part 3 – Model selection
- Part 4 – Model diagnostics
- Bayesian vs. frequentist inference
Instructors
- Mine Çetinkaya-Rundel - Department of Statistical Science
Content Designer
Platform
Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California.
Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.
Am truely impress with content, Platform and animation this site provides to learners. Looking forward to enrich my data analysis skills
Am truely impress with content, Platform and animation this site provides to learners. Looking forward to enrich my data analysis skills
